{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-18T09:44:09.920622Z",
     "iopub.status.busy": "2024-11-18T09:44:09.920150Z",
     "iopub.status.idle": "2024-11-18T09:44:15.648114Z",
     "shell.execute_reply": "2024-11-18T09:44:15.646811Z",
     "shell.execute_reply.started": "2024-11-18T09:44:09.920575Z"
    }
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append(\"src\")\n",
    "\n",
    "import os\n",
    "import torch\n",
    "\n",
    "from torch import nn\n",
    "from gradcam import GradCAM1D\n",
    "from dataset import ECGDataset\n",
    "from model import ConvNet\n",
    "from train import train_one_epoch\n",
    "from utils import *\n",
    "from torch.utils.data import DataLoader, Subset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "execution": {
     "iopub.execute_input": "2024-11-18T09:44:46.820149Z",
     "iopub.status.busy": "2024-11-18T09:44:46.818769Z",
     "iopub.status.idle": "2024-11-18T09:44:47.446042Z",
     "shell.execute_reply": "2024-11-18T09:44:47.444738Z",
     "shell.execute_reply.started": "2024-11-18T09:44:46.820079Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "archive\\mitbih_test.csv\n",
      "archive\\mitbih_train.csv\n",
      "archive\\ptbdb_abnormal.csv\n",
      "archive\\ptbdb_normal.csv\n"
     ]
    }
   ],
   "source": [
    "path = \"archive\"\n",
    "\n",
    "for dirpath, _, filenames in os.walk(path):\n",
    "    print(*[os.path.join(dirpath, i) for i in filenames], sep='\\n')    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-18T09:44:51.650169Z",
     "iopub.status.busy": "2024-11-18T09:44:51.649689Z",
     "iopub.status.idle": "2024-11-18T09:45:06.314848Z",
     "shell.execute_reply": "2024-11-18T09:45:06.313232Z",
     "shell.execute_reply.started": "2024-11-18T09:44:51.650124Z"
    }
   },
   "outputs": [],
   "source": [
    "mit_train = ECGDataset('archive/mitbih_train.csv')\n",
    "mit_test = ECGDataset('archive/mitbih_test.csv')\n",
    "ptb_normal = ECGDataset('archive/ptbdb_normal.csv')\n",
    "ptb_abnormal = ECGDataset('archive/ptbdb_abnormal.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "ptb = ptb_normal + ptb_abnormal\n",
    "indices = torch.randperm(len(ptb))\n",
    "ptb = Subset(ptb, indices)\n",
    "\n",
    "split_index = int(0.8 * len(ptb))\n",
    "ptb_train = Subset(ptb, torch.arange(0, split_index, 1))\n",
    "ptb_test = Subset(ptb, torch.arange(split_index, len(ptb), 1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training MIT-BIH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-18T09:48:30.326146Z",
     "iopub.status.busy": "2024-11-18T09:48:30.325704Z",
     "iopub.status.idle": "2024-11-18T09:48:30.338755Z",
     "shell.execute_reply": "2024-11-18T09:48:30.337329Z",
     "shell.execute_reply.started": "2024-11-18T09:48:30.326105Z"
    }
   },
   "outputs": [],
   "source": [
    "torch.manual_seed(42)\n",
    "\n",
    "model = ConvNet()\n",
    "\n",
    "optimizer = torch.optim.Adam(model.parameters(), lr=1e-4)\n",
    "loss_fn = nn.CrossEntropyLoss()\n",
    "dataloader = DataLoader(mit_train, batch_size=32, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-18T09:48:30.946085Z",
     "iopub.status.busy": "2024-11-18T09:48:30.945590Z",
     "iopub.status.idle": "2024-11-18T09:51:25.243634Z",
     "shell.execute_reply": "2024-11-18T09:51:25.241836Z",
     "shell.execute_reply.started": "2024-11-18T09:48:30.946041Z"
    }
   },
   "outputs": [],
   "source": [
    "EPOCHS = 1 \n",
    "\n",
    "# for epoch in range(EPOCHS):\n",
    "#     train_one_epoch(\n",
    "#         model,\n",
    "#         dataloader,\n",
    "#         optimizer,\n",
    "#         loss_fn,\n",
    "#         epoch,\n",
    "#         device='cuda'\n",
    "#     )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test MIT-BIH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-12T22:38:25.858709Z",
     "iopub.status.busy": "2024-11-12T22:38:25.857869Z",
     "iopub.status.idle": "2024-11-12T22:38:25.866560Z",
     "shell.execute_reply": "2024-11-12T22:38:25.865477Z",
     "shell.execute_reply.started": "2024-11-12T22:38:25.858661Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Accuracy: 95.96%\n",
      "Average F1-score: 0.9511\n",
      "Average Recall: 0.9596\n",
      "Average precision: 0.9494\n"
     ]
    }
   ],
   "source": [
    "state_dict = torch.load('weights/model.pt')\n",
    "\n",
    "model.load_state_dict(state_dict)\n",
    "\n",
    "test_dataloader = DataLoader(mit_test, batch_size=32, shuffle=True, drop_last=True)\n",
    "validate(model, test_dataloader)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training PTB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-12T22:56:04.177370Z",
     "iopub.status.busy": "2024-11-12T22:56:04.176959Z",
     "iopub.status.idle": "2024-11-12T22:56:04.184377Z",
     "shell.execute_reply": "2024-11-12T22:56:04.183119Z",
     "shell.execute_reply.started": "2024-11-12T22:56:04.177331Z"
    }
   },
   "outputs": [],
   "source": [
    "model_0 = ConvNet()\n",
    "model_0.load_state_dict(state_dict)\n",
    "\n",
    "model_0.classifier = nn.Sequential(nn.Flatten(start_dim=1, end_dim=-1),\n",
    "                              nn.Linear(in_features=128, out_features=32, bias=True),\n",
    "                              nn.ReLU(),\n",
    "                              nn.Linear(in_features=32, out_features=2, bias=True)\n",
    "                                  )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "for name, param in model_0.named_parameters():\n",
    "    if 'classifier' not in name:\n",
    "        param.requires_grad = False       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-12T23:11:24.844907Z",
     "iopub.status.busy": "2024-11-12T23:11:24.844459Z",
     "iopub.status.idle": "2024-11-12T23:11:24.852510Z",
     "shell.execute_reply": "2024-11-12T23:11:24.851418Z",
     "shell.execute_reply.started": "2024-11-12T23:11:24.844867Z"
    }
   },
   "outputs": [],
   "source": [
    "optimizer = torch.optim.Adam(model_0.parameters(), lr=1e-5)\n",
    "loss_fn = nn.CrossEntropyLoss()\n",
    "\n",
    "dataloader_ptb = DataLoader(ptb_train, batch_size=32, shuffle=True)\n",
    "\n",
    "model_0.to('cuda');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-12T23:11:26.129834Z",
     "iopub.status.busy": "2024-11-12T23:11:26.129374Z",
     "iopub.status.idle": "2024-11-12T23:11:48.417232Z",
     "shell.execute_reply": "2024-11-12T23:11:48.415868Z",
     "shell.execute_reply.started": "2024-11-12T23:11:26.129793Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# for epoch in range(5):\n",
    "#     train_one_epoch(\n",
    "#         model_0,\n",
    "#         dataloader_ptb,\n",
    "#         optimizer,\n",
    "#         loss_fn,\n",
    "#         epoch+1,\n",
    "#         device=\"cuda\"\n",
    "#     )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Accuracy: 91.17%\n",
      "Average F1-score: 0.9096\n",
      "Average Recall: 0.9117\n",
      "Average precision: 0.9159\n"
     ]
    }
   ],
   "source": [
    "state_dict_transfer = torch.load('weights/model_transfer.pt')\n",
    "model_0.load_state_dict(state_dict_transfer)\n",
    "\n",
    "test_dataloader = DataLoader(ptb_test, batch_size=32)\n",
    "validate(model_0, test_dataloader)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GradCam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "for name, param in model_0.named_parameters():\n",
    "        param.requires_grad = True       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = model_0\n",
    "target_layer = model.convnet[4].conv2\n",
    "gradcam = GradCAM1D(model, target_layer)\n",
    "\n",
    "i = 0\n",
    "input_tensor = ptb[i][0].unsqueeze(0)\n",
    "target_class = ptb[i][1]\n",
    "cam = gradcam.generate_cam(input_tensor, 0).squeeze().detach().numpy()\n",
    "cam1 = gradcam.generate_cam(input_tensor, 1).squeeze().detach().numpy()\n",
    "ecg_signal = input_tensor.squeeze().numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_ecg_with_background_cam(cam, ecg_signal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_ecg_with_background_cam(cam1, ecg_signal)"
   ]
  }
 ],
 "metadata": {
  "kaggle": {
   "accelerator": "none",
   "dataSources": [
    {
     "datasetId": 29414,
     "sourceId": 37484,
     "sourceType": "datasetVersion"
    }
   ],
   "dockerImageVersionId": 30786,
   "isGpuEnabled": false,
   "isInternetEnabled": true,
   "language": "python",
   "sourceType": "notebook"
  },
  "kernelspec": {
   "display_name": "pytorch",
   "language": "python",
   "name": "myenv.env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
